Evidence map›Paper›PMID 36052255›Full record

SynthesisFrontiers in oncology2022

Efficacy of immune checkpoint inhibitors in non-small cell lung cancer: A systematic review and meta-analysis.

Fang Yang, Yucai Wang, Lin Tang, Aaron Scott Mansfield, Alex A Adjei, Konstantinos Leventakos, Narjust Duma, Jia Wei, Lifeng Wang, Baorui Liu and 1 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
0.9field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Fang YangThe Comprehensive Cancer Center of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School & Clinical Cancer Institute of Nanjing University, Nanjing, China.
Yucai WangDivision of Hematology, Mayo Clinic, Rochester, MN, United States.
Lin TangDepartment of Rheumatology and Immunology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
Aaron Scott MansfieldDivision of Medical Oncology, Mayo Clinic, Rochester, MN, United States.
Alex A AdjeiDivision of Medical Oncology, Mayo Clinic, Rochester, MN, United States.
Konstantinos LeventakosDivision of Medical Oncology, Mayo Clinic, Rochester, MN, United States.
Narjust DumaLowe Center For Thoracic Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.
Jia WeiThe Comprehensive Cancer Center of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School & Clinical Cancer Institute of Nanjing University, Nanjing, China.
Lifeng WangThe Comprehensive Cancer Center of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School & Clinical Cancer Institute of Nanjing University, Nanjing, China.
Baorui LiuThe Comprehensive Cancer Center of Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School & Clinical Cancer Institute of Nanjing University, Nanjing, China.
Julian R MolinaDivision of Medical Oncology, Mayo Clinic, Rochester, MN, United States.
Nanjing Drum Tower Hospital · CNMayo Clinic in Arizona · USDana-Farber Cancer Institute · USMayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune checkpoint inhibitors (ICIs) have demonstrated remarkable efficacy in non-small cell lung cancer (NSCLC). However, only a minority of NSCLC patients benefit from ICIs, and whether the magnitude of benefit is specific factor-dependent remains unclear. We performed a systematic review to improve our understanding of clinicopathologic and biomolecular features associated with improved survival upon treatment with ICIs for NSCLC. Methods: We searched PubMed, Web of Science, Embase, and Scopus from database inception to August 31, 2021, for randomized controlled trials (RCTs) comparing overall survival (OS) in NSCLC treated with ICIs vs control therapies. We calculated the pooled OS hazard ratio (HR) and 95% CI in subgroups using a random-effects model, and assessed the heterogeneity between the paired estimates using an interaction test. Results: A total of 23 RCTs involving 15,829 patients were included. We found that wild-type EGFR, high PD-L1 expression, and high bTMB were associated with a significant OS benefit from ICIs, but not mutant EGFR, low PD-L1 expression, and low bTMB. The differences of OS benefit between wild-type and mutant EGFR (HR=1.53, 95%CI 1.13-2.08), high and low PD-L1 (HR=1.35; 95%CI 1.14-1.61), high and low bTMB (HR=1.71; 95%CI 1.17-2.52) were statistically significant. OS benefit was found in all subgroups regardless of sex, age, ECOG PS, histology, smoking history, baseline brain metastasis, race, and region, and the interaction test demonstrated no significant difference of the OS benefit between these opposed subgroups (e.g. male vs female). Conclusions: Wild-type EGFR, high PD-L1 expression, and high bTMB are associated with a greater magnitude of efficacy from ICIs vs control therapies in NSCLC. However, the administration of ICIs should not be restricted to other clinicopathological factors (sex, smoking history, race, etc.).

Indexed as

efficacyimmune checkpoint inhibitormeta-analysisnon-small cell lung cancersurvival

Identifiers

PMID36052255
PMCPMC9425065
OpenAlexW4292189024

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.